🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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Updated
Sep 30, 2024 - Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
Finetuning the Bert-based LLM to predict whether the tweet is toxic or not
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Minimalist NMT for educational purposes
Automatically split your PyTorch models on multiple GPUs for training & inference
HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
A little Python application to auto tag your photos with the power of machine learning.
Label data using HuggingFace's transformers and automatically get a prediction service
When Paint meets Artificial Intelligence! A Python application to generate pictures based on your drawing.
Instructions for how to convert a BERT Tensorflow model to work with HuggingFace's pytorch-transformers, and spaCy. This walk-through uses DeepPavlov's RuBERT as example.
State-of-the-art NLP through transformer models in a modular design and consistent APIs.
A bunch of Python scripts to create a Pokémon Classifier.
A little Python application to generate pictures from a text prompt. Based on Stable Diffusion.
A little Pokédex application that can find a Pokémon in any image with the power of machine learning.
Source code for "LIMIT-BERT : Linguistics Informed Multi-Task BERT" published at Findings of EMNLP 2020
Forecasting open-high-low-close (OHLC) data with Transformer models
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
Utilizing webscraping and state-of-the-art NLP to generate TV show episode summaries.
医药知识图谱自动问答系统实现,包括构建知识图谱、基于知识图谱的流水线问答以及前端实现。实体识别(基于词典+BERT_CRF)、实体链接(Sentence-BERT做匹配)、意图识别(基于提问词+领域词词典)。
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